class_docstr: The Luma Get Event Table implementation
docstr: Pulls data from the https://docs.lu.ma/reference/get-event-1 and https://docs.lu.ma/reference/calendar-list-events" API
  
  Parameters
  ----------
  query : ast.Select
     Given SQL SELECT query
  
  Returns
  -------
  pd.DataFrame
      Luma events
  
  Raises
  ------
  ValueError
      If the query contains an unsupported condition
docstr_tok: ["Pulls","data","from","the","https",":","\/\/docs.lu.ma\/reference\/get-event-1","and","https",":","\/\/docs.lu.ma\/reference\/calendar-list-events","''","API","Parameters","--","--","--","--","--","query",":","ast.Select","Given","SQL","SELECT","query","Returns","--","--","--","-","pd.DataFrame","Luma","events","Raises","--","--","--","ValueError","If","the","query","contains","an","unsupported","condition"]
code: def select(self, query: ast.Select) -> pd.DataFrame:
      """Pulls data from the https://docs.lu.ma/reference/get-event-1 and https://docs.lu.ma/reference/calendar-list-events" API
  
      Parameters
      ----------
      query : ast.Select
         Given SQL SELECT query
  
      Returns
      -------
      pd.DataFrame
          Luma events
  
      Raises
      ------
      ValueError
          If the query contains an unsupported condition
      """
  
      select_statement_parser = SELECTQueryParser(
          query, "events", self.get_columns()
      )
  
      (
          selected_columns,
          where_conditions,
          order_by_conditions,
          result_limit,
      ) = select_statement_parser.parse_query()
  
      search_params = {}
      subset_where_conditions = []
      filter_flag = False
      for op, arg1, arg2 in where_conditions:
          if arg1 == "event_id":
              if op == "=":
                  search_params["event_id"] = arg2
                  filter_flag = True
              else:
                  raise NotImplementedError(
                      "Only '=' operator is supported for event_id column."
                  )
          elif arg1 in self.get_columns():
              subset_where_conditions.append([op, arg1, arg2])
  
      df = pd.DataFrame(columns=self.get_columns())
  
      if filter_flag:
          response = self.handler.luma_client.get_event(
              search_params["event_id"]
          )
          event = response["content"]["event"]
          df = pd.json_normalize(event)
      else:
          response = self.handler.luma_client.list_events()
          content = response["content"]["entries"]
          events_only = [event["event"] for event in content]
          df = pd.json_normalize(events_only)
  
      select_statement_executor = SELECTQueryExecutor(
          df,
          selected_columns,
          subset_where_conditions,
          order_by_conditions,
          result_limit,
      )
  
      df = select_statement_executor.execute_query()
  
      return df
  
file_path: mindsdb/mindsdb/integrations/handlers/luma_handler/luma_tables.py
imports: import pandas
  from mindsdb.integrations.libs.api_handler import APITable
  from mindsdb.integrations.handlers.utilities.query_utilities import SELECTQueryParser, SELECTQueryExecutor, INSERTQueryParser
  from mindsdb_sql.parser import ast
label_desc: Use image node_id 1 for calling the LumaEventsTable obj's underlying member method code with example usage: obj.select(query) and returns: df